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Inc."},"license":"Apache-2.0","homepage":"https://picovoice.ai/products/porcupine/","keywords":["porcupine, picovoice, wake word, hotword, trigger word, offline, private, voice ai, speech recognition, microphone, mic, realtime"],"repository":{"url":"git+https://github.com/Picovoice/porcupine.git","type":"git","directory":"demo/nodejs"},"description":"Picovoice Porcupine Node.js file-based and microphone demos","maintainers":[{"email":"kyeo@picovoice.ai","name":"kyeo"},{"email":"alireza@picovoice.ai","name":"kenarsa"},{"email":"ian@picovoice.ai","name":"ilavery"},{"email":"eric@picovoice.ai","name":"erismikpico"},{"email":"matthew@picovoice.ai","name":"matt200-ok"},{"email":"gabriel@picovoice.ai","name":"gabe-picovoice"}],"readme":"# Porcupine Node.js Demos\n\nThis package provides two demonstration command-line applications for Porcupine: a file based demo, which scans a compatible WAV file for keywords, and a microphone demo, which listens for keywords and outputs detections live.\n\n## Introduction to Porcupine\n\nPorcupine is a highly accurate and lightweight wake word engine. It enables building always-listening voice-enabled applications using cutting edge voice AI.\n\nPorcupine is:\n\n- private and offline\n- [accurate](https://github.com/Picovoice/wake-word-benchmark)\n- [resource efficient](https://www.youtube.com/watch?v=T0tAnh8tUQg) (runs even on microcontrollers)\n- data efficient (wake words can be easily generated by simply typing them, without needing thousands of hours of bespoke audio training data and manual effort)\n- scalable to many simultaneous wake-words / always-on voice commands\n- cross-platform\n\nTo learn more about Porcupine, see the [product](https://picovoice.ai/products/porcupine/), [documentation](https://picovoice.ai/docs/), and [GitHub](https://github.com/Picovoice/porcupine/) pages.\n\n## Compatibility\n\nThese demos run Porcupine on **Node.js 18+** on the following platforms:\n\n- Windows (x86_64, arm64)\n- Linux (x86_64)\n- macOS (x86_64, arm64)\n- Raspberry Pi (3, 4, 5)\n\n### Web Browsers\n\nThese demos and the bindings upon which they are built are for Node.js and **do not work in a browser**. Looking to run Porcupine in-browser? See the [@picovoice/porcupine-web](https://www.npmjs.com/package/@picovoice/porcupine-web)<!-- markdown-link-check-disable-line --> package.\n\n## AccessKey\n\nPorcupine requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using Porcupine SDKs.\nYou can get your `AccessKey` for free. Make sure to keep your `AccessKey` secret.\nSignup or Login to [Picovoice Console](https://console.picovoice.ai/) to get your `AccessKey`.\n\n### Microphone demo\n\nThe microphone demo allows you monitor microphone input for keywords using Porcupine.\n\n## Install NPM package\n\nTo install the demos and make them available on the command line, use either of the following `yarn` or `npm` commands:\n\n```console\nyarn global add @picovoice/porcupine-node-demo\n```\n\n(or)\n\n```console\nnpm install -g @picovoice/porcupine-node-demo\n```\n\n### Run the mic demo\n\nUse `ppn-mic-demo` to run the mic demo. First select an input audio device to start recording audio:\n\n```console\nppn-mic-demo --show_audio_devices\n```\n\nThis command prints a list of the available devices and its inputs:\n\n```console\nindex: 0, device name: USB Audio Device\nindex: 1, device name: MacBook Air Microphone\n```\n\nSpecify the input audio device with `--audio_device_index` and either built-in\nkeywords with `--keywords` or paths to Porcupine `.ppn` files with `--keyword_file_paths`.\nProvide your Picovoice AccessKey with `--access_key`.\n\nHere is an example using Audio Device Index which will listen for \"grapefruit\" keyword:\n\n```console\nppn-mic-demo \\\n--access_key ${ACCESS_KEY} \\\n--keywords grapefruit \\\n--audio_device_index 0\n```\n\nWake word detections will display in the console:\n\n```console\n$ ppn-mic-demo --access_key ${ACCESS_KEY} --keywords grapefruit\nUsing device: USB Audio Device\nListening for wake word(s): grapefruit\nPress ctrl+c to exit.\n\n...\n\nDetected 'grapefruit'\n```\n\n### Run the file demo\n\nThe file-based demo allows you to scan a compatible wave file for keywords using Porcupine. Note: **The demo requires 16KHz, 16-bit linear PCM, single-channel (mono) WAV files**.\n\nTo run the file-based demo,\n\ne.g. check the input wave file for the built-in keywords \"grasshopper\" and \"bumblebee\" against the audio sample that is included with the porcupine repository:\n\n```console\nppn-file-demo \\\n--access_key ${ACCESS_KEY} \\\n--input_audio_file_path ../../resources/audio_samples/multiple_keywords.wav \\\n--keywords grasshopper,bumblebee\n```\n\nDetections of each keyword will be output in the terminal, along with their time location in the file:\n\n```console\nppn-file-demo \\\n--access_key ${ACCESS_KEY} \\\n--input_audio_file_path ../../resources/audio_samples/multiple_keywords.wav \\\n--keywords grasshopper\nDetected keyword 'bumblebee' @ 16.096s\nDetected keyword 'grasshopper' @ 28.896s\n```\n\n## Common Demo Options\n\nThe microphone and file demos both have additional options.\n\nTo see the full set of options, use `--help`:\n\n```console\nppn-mic-demo --help\n```\n\n```console\nppn-file-demo --help\n```\n\n```console\nUsage: ppn-file-demo [options]\n\nOptions:\n  -i, --input_audio_file_path <string>  input audio wave file in 16-bit 16KHz linear PCM format (mono)\n  -a, --access_key <string>             AccessKey obtain from the Picovoice Console (https://console.picovoice.ai/)\n  -k, --keyword_file_paths <string>     absolute path(s) to porcupine keyword files (.ppn)\n  -b, --keywords <string>               built in keyword(s)\n                                        (americano,blueberry,bumblebee,grapefruit,grasshopper,picovoice,porcupine,terminator)\n  -l, --library_file_path <string>      absolute path to porcupine dynamic library\n  -m, --model_file_path <string>        absolute path to porcupine model\n  -s, --sensitivity <number>            sensitivity value between 0 and 1 (default: 0.5)\n  -h, --help                            display help for command\n```\n\n### Sensitivity\n\nThe sensitivity is a floating point value in the range [0,1] which specifies the tradeoff between miss rate and false alarm. The demo defaults to 0.5. You can override this with `--sensitivity`:\n\n```console\nppn-mic-demo \\\n--access_key ${ACCESS_KEY} \\\n--input_audio_file_path ../../resources/audio_samples/multiple_keywords.wav \\\n--keywords bumblebee \\\n--sensitivity 0.65\n```\n\n### Custom keyword (ppn) files\n\nPorcupine includes several built-in keywords, which are stored as `.ppn` files. To train custom PPN files, see the [Picovoice Console](https://console.picovoice.ai/).\n\nUnlike the built-in keywords, custom PPN files generated with the Picovoice Console carry restrictions including (but not limited to): training allowance, time limits, available platforms, and commercial usage.\n\n#### Providing custom ppn files\n\nYou can specify non-builtin keywords as absolute paths to `.ppn` keyword files, using `--keyword_file_paths`. The PPN keyword files must be compatible with the platform you are running.\n\ne.g. for Linux (x86_64), using two keywords: \"bumblebee\" and \"grasshopper\":\n\n```console\nppn-file-demo \\\n--access_key ${ACCESS_KEY} \\\n--input_audio_file_path ../../resources/audio_samples/multiple_keywords.wav \\\n--keyword_file_paths ../../resources/keyword_files/linux/grasshopper_linux.ppn,../../resources/keyword_files/linux/bumblebee_linux.ppn\n```\n\n### Custom library and model files\n\nYou may override the porcupine model and dynamic libraries by specifying their absolute paths with `--model_file_path` and `--library_file_path`, respectively. As with keyword files, the dynamic library is specific to the platform.\n\ne.g. for macOS (x86_64, arm64):\n\n```console\nppn-file-demo \\\n--access_key ${ACCESS_KEY} \\\n--input_audio_file_path ../../resources/audio_samples/multiple_keywords.wav \\\n--keywords terminator \\\n--library_file_path ../../lib/mac/x86_64/libpv_porcupine.dylib \\\n--model_file_path ../../lib/common/porcupine_params.pv\n```\n\n## Running the demos from the GitHub repository\n\nUse one of `yarn` or `npm` to install the package dependencies from the demo/nodejs folder:\n\n```console\ncd demo/nodejs\nyarn\n```\n\n(or)\n\n```console\ncd demo/nodejs\nnpm install\n```\n\n### Microphone demo\n\nUse `yarn mic` (or `npm run mic`) to run the mic demo from the demos/nodejs directory. For `npm run`, note the extra `--` needed before specifying commands. This is to disambiguate whether the options are intended for npm or for the demo script.\n\n```console\nyarn mic --access_key ${ACCESS_KEY} --keywords grapefruit\n```\n\n(or)\n\n```console\nnpm run mic -- --access_key ${ACCESS_KEY} --keywords grapefruit\n```\n\n### File demo\n\nUse `yarn file` or `npm run file` from the `demos/nodejs` directory. For `npm run`, note the extra `--` needed before specifying commands. This is to disambiguate whether the options are intended for npm or for the demo script.\n\n```console\nyarn file --access_key ${ACCESS_KEY} \\\n--input_audio_file_path ../../resources/audio_samples/multiple_keywords.wav \\\n--keywords grasshopper\n```\n\n(or)\n\n```console\nnpm run file -- --access_key ${ACCESS_KEY} \\\n--input_audio_file_path ../../resources/audio_samples/multiple_keywords.wav \\\n--keywords grasshopper\n```\n","readmeFilename":"README.md"}